VLMs show a resolution illusion on UHR Earth observation imagery where higher resolution does not improve micro-target perception; UHR-Micro benchmark and MAP-Agent address this via evidence-centered active inspection.
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SkyNative introduces an encoder-free architecture using raw patch tokens and modality-specific parameters in a unified autoregressive model to improve image-grounded reasoning in remote sensing vision-language tasks.
Seed2.0 model series reports gains in reasoning, visual understanding, search, and reliability on intricate long-horizon tasks via an internal evaluation system.
citing papers explorer
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UHR-Micro: Diagnosing and Mitigating the Resolution Illusion in Earth Observation VLMs
VLMs show a resolution illusion on UHR Earth observation imagery where higher resolution does not improve micro-target perception; UHR-Micro benchmark and MAP-Agent address this via evidence-centered active inspection.
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SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning
SkyNative introduces an encoder-free architecture using raw patch tokens and modality-specific parameters in a unified autoregressive model to improve image-grounded reasoning in remote sensing vision-language tasks.
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Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity
Seed2.0 model series reports gains in reasoning, visual understanding, search, and reliability on intricate long-horizon tasks via an internal evaluation system.